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Jun, 2020
COVID-19 疫情对齐的跨语言迁移学习
Cross-lingual Transfer Learning for COVID-19 Outbreak Alignment
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Sharon Levy, William Yang Wang
TL;DR
本研究通过对意大利 COVID-19 疫情疫情的 Twitter 数据进行学习，并使用跨语言迁移学习模型对多个国家的疫情进行预测，结果显示在跨国预测中有高达 0.85 的斯皮尔曼相关性。
Abstract
The spread of
covid-19
has become a significant and troubling aspect of society in 2020. With millions of cases reported across countries, new outbreaks have occurred and followed patterns of previously affected areas. Many
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